An Agent-Based Modeling and Virtual Reality Application Using Distributed Simulation: Case of a COVID-19 Intensive...

Area of Science:

• Healthcare Operations Research
• Medical Simulation Technology
• Infectious Disease Modeling

Background:

• Simulation methods are crucial for hospital operations, management, and training.
• The COVID-19 pandemic underscored the need for advanced modeling and simulation, especially distributed simulation (DS), for rapid remote assessment.
• DS integrates diverse simulations to boost overall effectiveness and usability.

Purpose of the Study:

• To present a distributed simulation (DS) system integrating two distinct simulations for a COVID-19 intensive care unit (ICU).
• To demonstrate the system's utility for training and assessing managerial/operational decisions aimed at reducing contact and disease spread.
• To leverage DS for enhanced data exchange and synchronized operation between simulation platforms.

Main Methods:

• Developed an AnyLogic simulation model of an ICU ward using agent-based and discrete event methods to depict healthcare provider-patient contacts.
• Created a virtual reality simulation of the ICU environment and operations using the Unity platform.
• Integrated and synchronized both simulations using a cloud-based DS system adhering to the IEEE high-level architecture standard.

Main Results:

• The integrated DS system enhanced the capabilities of both individual simulations.
• The system facilitates data exchange between the AnyLogic and Unity platforms.
• The DS system provides a platform for effective training and assessment of operational strategies.

Conclusions:

• The developed cloud-based DS system effectively integrates heterogeneous simulations for a COVID-19 ICU.
• This approach supports improved training and decision-making for minimizing disease transmission in critical care settings.
• Distributed simulation offers a powerful tool for enhancing healthcare operational efficiency and patient safety.